Clio: a 5-μm camera for the detection of giant exoplanets
Bibliographic record
Abstract
We plan to take advantage of the unprecedented combination of low thermal background and high resolution provided by the 6.5m MMT's adaptive secondary mirror, to target the 3-5 micron atmospheric window where giant exoplanets are expected to be anomalously bright. We are in the process of building a 3-5 micron camera that we will use to carry out a survey to characterize the prevalence and distribution of giant planets around nearby, Sun-like stars. Sensitivity estimates show that for a 1 Gyr old G0V primary at 10 pc, we expect to detect 5 MJupiter and 15 MJupiter exoplanets at angular separations greater than 0.45-2.1" and 0.2-1.2" respectively. Monte Carlo simulations based on these sensitivity estimates and a sample of 80 young (<1 Gyr), nearby (<20 pc) M0V-F0V stars, predict the detection of 15±3 exoplanets with masses of 4-15 MJupiter and separations of 17-50 AU. Construction of the camera is currently underway and on-telescope testing is expected in the Fall 2004-Winter 2005.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".